Neonatal sepsis is a life-threatening blood infection frequently affecting premature babies. Early detection is critical for full recovery. Our approach tries to achieve this by carefully modelling the dynamics of the patient's vital signs. Crucially, patterns in the monitoring data can be associated with clinical events. Some of these are acknowledged to be symptoms for the onset of sepsis. We use this knowledge to build a hierarchical model which develops on the switching and factorization ideas for generalizing state-space models. We then show that Markov modelling of clinical events is able to produce correct on-line inferences for both a group of sepsis patients and for a control one.

Robert Court

Investigating neural plasticity within the thoracico-abdominal ganglion of Drosophila

Neural circuits are difficult to isolate from the surrounding system without affecting their function. In order to computationally and experimentally dissect these circuits it is not only ideal to minimise any interference but also be able to genetically target each part of the circuit. In this talk, I will discuss how we plan to map the functional connectome of the Drosophila ganglions using neural lineage markers and how this will enable investigation of simple behavioural circuits that demonstrate neural plasticity.